Spatial distribution of common childhood illnesses, healthcare utilisation and associated factors in Ethiopia: Evidence from 2016 Ethiopian Demographic and Health Survey

• Published in: PloS one 2023-03, Vol.18 (3), p.e0281606-e0281606
• Main Authors: Defar, Atkure, B Okwaraji, Yemisrach, Tigabu, Zemene, Persson, Lars Åke, Alemu, Kassahun
• Format: Article
• Language: English
• Subjects: Age; Caregivers; Child; Child, Preschool; Childhood; Children; Children & youth; Childrens health; Clustering; Delivery of Health Care; Demographics; Demography; Diarrhea; Diseases; Earth Sciences; Ethiopia - epidemiology; Fever; Geographical distribution; Geography; Geospatial data; Global positioning systems; GPS; Health aspects; Health care; Health care facilities; Health facilities; Health problems; Health services; Health services utilization; Health Surveys; Households; Humans; Illnesses; Interpolation; Kriging interpolation; Low income areas; Low level; Medical care; Medicine and Health Sciences; Methods; Mothers; Patient Acceptance of Health Care; People and Places; Physical Sciences; Poverty; Public health; Questionnaires; Rural areas; Sea level; Spatial Analysis; Spatial data; Spatial distribution; Spatial variations; Statistical analysis; Surveys; Surveys and Questionnaires; Utilization
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0281606

Childhood illnesses, such as acute respiratory illness, fever, and diarrhoea, continue to be public health problems in low-income countries. Detecting spatial variations of common childhood illnesses and service utilisation is essential for identifying inequities and call for targeted actions. This study aimed to assess the geographical distribution and associated factors for common childhood illnesses and service utilisation across Ethiopia based on the 2016 Demographic and Health Survey. The sample was selected using a two-stage stratified sampling process. A total of 10,417 children under five years were included in this analysis. We linked data on their common illnesses during the last two weeks and healthcare utilisation were linked to Global Positioning System (GPS) information of their local area. The spatial data were created in ArcGIS10.1 for each study cluster. We applied a spatial autocorrelation model with Moran's index to determine the spatial clustering of the prevalence of childhood illnesses and healthcare utilisation. Ordinary Least Square (OLS) analysis was done to assess the association between selected explanatory variables and sick child health services utilisation. Hot and cold spot clusters for high or low utilisation were identified using Getis-Ord Gi*. Kriging interpolation was done to predict sick child healthcare utilisation in areas where study samples were not drawn. All statistical analyses were performed using Excel, STATA, and ArcGIS. Overall, 23% (95CI: 21, 25) of children under five years had some illness during the last two weeks before the survey. Of these, 38% (95%CI: 34, 41) sought care from an appropriate provider. Illnesses and service utilisation were not randomly distributed across the country with a Moran's index 0.111, Z-score 6.22, P